• DocumentCode
    420959
  • Title

    Neural networks based parallel Viterbi decoder by hybrid design

  • Author

    Dong, Lin ; Wentao, Song ; Xingzhao, Liu ; Hanwen, Luo ; Youyun, Xu ; Wenjun, Zhang

  • Author_Institution
    Dept. of Electron. Eng., Shanghai Jiaotong Univ., China
  • Volume
    3
  • fYear
    2004
  • fDate
    15-19 June 2004
  • Firstpage
    1923
  • Abstract
    A hybrid scheme integrating analog and digital methods is presented to design a Viterbi decoder based on neural networks. Due to its fully parallel architecture, neural networks based Viterbi decoder is significantly faster than the purely digital decoder. The fully parallel structure is obtained by implementing the branch metric calculation and add-compare-select (ACS) using the neural networks while the register exchange using parallel digital circuits. The hybrid Viterbi decoder is more suitable for VLSI implementation.
  • Keywords
    VLSI; Viterbi decoding; digital circuits; hybrid integrated circuits; integrated circuit design; maximum likelihood estimation; neural nets; parallel architectures; VLSI; add-compare-select; analog integrating method; branch metric calculation; digital decoder; digital integrating method; hybrid Viterbi decoder; hybrid design; maximum likelihood estimation; neural networks; parallel Viterbi decoder; parallel architecture; parallel digital circuits; parallel structure; register exchange; Convolution; Convolutional codes; Costs; Digital circuits; Maximum likelihood decoding; Neural networks; Parallel architectures; Registers; Very large scale integration; Viterbi algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
  • Print_ISBN
    0-7803-8273-0
  • Type

    conf

  • DOI
    10.1109/WCICA.2004.1341914
  • Filename
    1341914